Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Componential Analysis (Ethnographic)× | Cultural Domain Analysis× | |
|---|---|---|
| Nyanja | Anthropology | Anthropology |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1979 | 1994 |
| Mwanzilishi≠ | Ethnoscience tradition (Goodenough, Lounsbury; systematized by Spradley) | Stephen P. Borgatti (synthesis of cognitive anthropology methods) |
| Aina≠ | Feature-based analysis of contrasts within a folk domain | Integrated framework for eliciting and analyzing cultural domains |
| Chanzo asilia≠ | Spradley, J. P. (1979). The Ethnographic Interview. New York: Holt, Rinehart and Winston. ISBN: 9780030444968 | Borgatti, S. P. (1994). Cultural domain analysis. Journal of Quantitative Anthropology, 4(4), 261–278. link ↗ |
| Majina mbadala | Ethnographic Componential Analysis, Feature Analysis of Kin and Folk Terms, Componential Analysis of Meaning, Contrast-Set Feature Analysis | CDA, Domain Analysis (cognitive anthropology), Cultural Domains Approach, Cognitive Domain Analysis |
| Zinazohusiana≠ | 3 | 4 |
| Muhtasari≠ | Ethnographic componential analysis is the analytic step that specifies the meaning of folk terms by laying out the distinctive attributes — the components — that distinguish each term from the others in the same contrast set. Rooted in the ethnoscience study of kinship terminologies and systematized within Spradley's Developmental Research Sequence, it builds a paradigm: a grid of terms against the dimensions of contrast that defines exactly what makes, say, an 'uncle' different from a 'cousin' in a given culture's own logic. | Cultural domain analysis is the integrated framework in cognitive anthropology for discovering the content and structure of a cultural domain — a coherent set of related items such as illnesses, animals, kin terms, or emotions — as the members of a culture themselves organize it. It chains together elicitation methods (free listing, pile sorting, triad tests) and analytic methods (salience, multidimensional scaling, clustering, consensus analysis) to move from 'what items are in this domain?' to 'how are they organized and how widely is that organization shared?' |
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